In general, retailers manage product information and specifications for the products and services they offer using data from manufacturers and suppliers. They also obtain and use customer data in one of two ways. In a first traditional way, retailers can acquire data from one or more big data sources already aggregated in segments. They use the acquired data in order to create product or service clusters or segments, then analyze the created clusters or segments, and are able to predict future purchases of a consumer segment. The acquired data may include personal data of the consumer from social networking sites, or other sources of personal data, or purchasing data and/or location-based records (e.g., from a cellular network, search engine, and/or mapping or geolocation company), any or all of which is aggregated at the source when regulations require.
In a second way, retailers can also acquire personal data from aggregators, such as Enliken, Intelius, Spokeo, etc., and use the personal data to predict future purchases or desires. A retailer may also use personal data it collected itself from customers, including personal data (e.g., address, age, etc.), transactional data, and/or wishlists, either in isolation or in combination with other acquired data.
The traditional approach to providing both in-store and online shopping experiences is to cause the consumer to spend as much time as possible in the store or on the website. Many retailers believe that a shopper spending more time in a shopping experience, is the only method to generate more sales as a result of additional time spent shopping by the consumer.
Today, the quality of big data available is not sufficient to ensure that the costs of a retailer acquiring, storing and processing the data outweigh the benefits of the use of the big data. While correlation with a purchasing behavior can be established in a given segment, the causality is far from being clear and the proper use of the results can be doubtful. In addition, consumers have increasingly become sensitive to sharing personal or identifying data with retailers beyond information necessary to make a purchase. In some cases, a consumer may input false data to prevent future contact from the retailer if the consumer perceives future contact as annoying or intrusive.
Governments and organizations are also becoming more involved with regulating acquisition and storage of consumer data due to occasional data leaks of personally identifiable information and financial information, and are considering forcing retailers and other online entities to implement privacy rules. Furthermore, increasing numbers of consumers manage personal data on smartphones and mobile devices locally and use the data in transactions as needed, which provides less available data to retailers. With less available data about consumers, a retailer can have difficulty providing accurate product recommendations to its consumers. Retailers may also realign their assets towards shopper service over data crunching.